Job DescriptionThe Senior MLOps Engineer will be responsible for designing, implementing, and managing the end-to-end operational lifecycle of Machine Learning and Generative AI models. This includes model packaging, deployment, CI/CD automation, model monitoring, infrastructure management, governance, observability, and continuous optimization.The role requires solid expertise in cloud infrastructure, DevOps, Kubernetes, ML platforms, model lifecycle management, and enterprise-scale AI deployment.The ideal candidate will work closely with AI Engineers, Data Scientists, ML Engineers, AI Platform Engineers, Enterprise Architecture, Infrastructure, Information Security, and Digital Engineering teams to operationalize AI across the enterprise.## MLOps Platform Strategy- Design and implement the enterprise MLOps platform.- Define the operating model for AI and ML deployments.- Establish standards for model lifecycle management.- Develop reusable deployment templates and automation frameworks.- Build scalable AI deployment capabilities across cloud and on-premise environments.- Define engineering best practices for AI operations.## Machine Learning Lifecycle ManagementManage The Complete Lifecycle Of AI/ML Models Including- Model Registration- Version Control- Model Packaging- Model Validation- Model Deployment- Model Promotion- Model Rollback- Model Retirement- Model ArchivingImplement automated governance throughout the ML lifecycle.## CI/CD for AIDevelop Automated CI/CD Pipelines For- Machine Learning Models- Generative AI Applications- AI APIs- Feature Engineering Pipelines- Data Validation Pipelines- Model Testing- Prompt Evaluation- AI Agent DeploymentsIntegrate deployment pipelines with enterprise DevOps processes.## Production DeploymentDeploy AI Solutions Across Enterprise Platforms Including- Loan Origination Systems- CRM- Mobile Applications- Customer Portals- Contact Centre Platforms- Collections Platforms- Enterprise Data Lake- Marketing Automation Platforms- Digital Payment Platforms- API GatewayEnsure high availability, resilience, scalability, and fault tolerance.## Model Monitoring & ObservabilityBuild Monitoring Capabilities For- Model Accuracy- Data Drift- Concept Drift- Prompt Performance- Latency- API Response Time- Infrastructure Utilization- GPU Utilization- Business KPIs- Cost OptimizationDevelop dashboards and automated alerts for production AI systems.## Infrastructure AutomationDesign And Manage AI Infrastructure Using- Infrastructure as Code (IaC)- Containerization- Kubernetes Orchestration- Auto Scaling- GPU Resource Management- High Availability Architecture- Disaster Recovery- Backup & Restore- Capacity Planning## Feature Store & Model RegistryDevelop And Maintain Enterprise- Feature Store- Model Registry- Experiment Tracking- Artifact Repository- Metadata RepositoryEnsure consistency and reusability across AI initiatives.## Generative AI OperationsOperationalize Enterprise GenAI Applications Including- Large Language Models (LLMs)- Retrieval-Augmented Generation (RAG)- AI Agents- Prompt Libraries- Vector Databases- Knowledge Bases- AI Search- Enterprise AI CopilotsManage prompt versioning, model evaluation, and deployment pipelines.## Security & ComplianceImplement Security Best Practices For AI Deployments Including- Role-Based Access Control (RBAC)- Secrets Management- API Security- Identity & Access Management- Encryption- Vulnerability Management- Audit Logging- Secure Model Deployment- Compliance with enterprise security standardsCollaborate with Information Security and AI Governance teams.# Educational Qualifications- Bachelor's Degree in Computer Science, Information Technology, Engineering, Artificial Intelligence, Data Science, or related discipline.# Experience- 5-8 years of experience in DevOps, Cloud Engineering, MLOps, or AI Platform Engineering.- Minimum 3 years of experience operationalizing machine learning models in production.- Experience managing cloud-native AI platforms.- Experience in Banking, NBFC, Financial Services, or FinTech is preferred.

📌 Chief Manager - Application (Maharashtra)
🏢 HDB Financial Services
📍 Maharashtra